Instructions to use yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning/resolve/main/training_args.bin
- Command line
-
hf download hf://yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/yigitkucuk/SmolLM2-360M-SFT-ConciseReasoning/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- f558a802842e0c54cf688844ee536a3a27717e941b2260d916f958557c31009f
- Size of remote file:
- 5.69 kB
- SHA256:
- a90c60fd5361b7b785f32f06aaba2177b675d5d5f397866ddaad128713035ac6
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